OpenClaw + Todoist: Real-Time Task Visibility for Long Agent Runs

Long-running agent workflows are powerful, but they often feel like a black box. You ask OpenClaw to build, research, refactor, or write, then you wait. If you come back an hour later, you have to re-read chat logs to understand what happened.

This guide shows how to turn Todoist into a live “agent run console”: OpenClaw creates a task for each big mission, writes its plan into the task description, and streams step-by-step progress as comments. You get transparency, a timeline, and a single place to check status, even when the agent is working in the background.

Internal links you may want open in a tab:

• /blog/openclaw-use-cases
• /blog/openclaw-skills-guide

What you will build

A lightweight task visibility system that:

• Creates a Todoist task for every complex OpenClaw run
• Moves the task between sections like In Progress, Waiting, Done
• Externalizes the agent plan into the task description
• Streams milestone logs as comments in real time
• Optionally detects stalled runs and pings you

It is not meant to replace your real project tracker. It is a visibility layer.

Why Todoist works well for agent visibility

Todoist has three properties that make it an excellent “external state store” for agent runs:

1. Fast mobile access: you can check status without opening a laptop.
2. Comments as an append-only timeline: progress becomes auditable.
3. Sections as state: you can scan what is running versus blocked.

The goal is to reduce anxiety and re-entry cost. You should never wonder “what is the agent doing right now?”

Skills and tools required

From an OpenClaw perspective, you need:

• A deployed OpenClaw agent (ClawRapid recommended for reliability)
• Shell access or the ability for the agent to create and run local scripts
• Todoist API access (a personal API token)

You do not need a pre-built Todoist skill to get value. The approach below uses a tiny bash wrapper around Todoist’s REST API.

If you are new to installing and configuring skills, read: /blog/openclaw-skills-guide

High-level architecture

• You create a Todoist project called “OpenClaw Workspace”.
• Inside it, you create sections representing status.
• OpenClaw calls the Todoist REST API:
  • Create or update a task
  • Move tasks by setting section_id
  • Add comments for progress logs

This works because Todoist is effectively a simple database with a nice UI.

Step-by-step setup

Step 1: Create a Todoist project and sections

In Todoist:

1. Create a new project: “OpenClaw Workspace”.
2. Add three sections:

• 🟡 In Progress
• 🟠 Waiting
• 🟢 Done

Optional sections that many people add later:

• 🔴 Blocked (for external blockers)
• 🧪 Experiments (small R and D tasks)

Step 2: Generate a Todoist API token

In Todoist, go to Settings and find your personal API token.

Security note: treat it like a password. Do not paste it into public repos, and do not hardcode it into scripts that might be committed.

Step 3: Get the Project ID and Section IDs

You need:

• Project ID for “OpenClaw Workspace”
• Section IDs for each status section

The simplest method is to have OpenClaw query the API once you provide the token.

Prompt:

I want to set up a Todoist visibility system for your long runs.

Use my Todoist API token (I will paste it next).

1) List my Todoist projects and find the project named "OpenClaw Workspace".
2) List the sections in that project and return the section IDs for:
- 🟡 In Progress
- 🟠 Waiting
- 🟢 Done

Return a single JSON object with project_id and the 3 section_ids.

Step 4: Create the minimal scripts

Ask OpenClaw to create three scripts in a scripts/ directory:

1. todoist_api.sh: core curl wrapper
2. sync_task.sh: create or update a task and place it in the correct section
3. add_comment.sh: append progress logs as comments

Reference implementation (adapt token storage to your environment):

#!/bin/bash
# scripts/todoist_api.sh
# Usage: ./todoist_api.sh <endpoint> <method> [data_json]
ENDPOINT=$1
METHOD=$2
DATA=$3
TOKEN="$TODOIST_API_TOKEN"

if [ -z "$DATA" ]; then
  curl -s -X "$METHOD" "https://api.todoist.com/rest/v2/$ENDPOINT" \
    -H "Authorization: Bearer $TOKEN"
else
  curl -s -X "$METHOD" "https://api.todoist.com/rest/v2/$ENDPOINT" \
    -H "Authorization: Bearer $TOKEN" \
    -H "Content-Type: application/json" \
    -d "$DATA"
fi

#!/bin/bash
# scripts/sync_task.sh
# Usage: ./sync_task.sh <task_content> <status> [task_id] [description] [labels_json_array]
CONTENT=$1
STATUS=$2
TASK_ID=$3
DESCRIPTION=$4
LABELS=$5
PROJECT_ID="$TODOIST_PROJECT_ID"

case $STATUS in
  "In Progress") SECTION_ID="$TODOIST_SECTION_PROGRESS" ;;
  "Waiting")     SECTION_ID="$TODOIST_SECTION_WAITING"  ;;
  "Done")        SECTION_ID="$TODOIST_SECTION_DONE"     ;;
  *)             SECTION_ID=""                           ;;
esac

PAYLOAD="{\"content\": \"$CONTENT\""
[ -n "$SECTION_ID" ] && PAYLOAD="$PAYLOAD, \"section_id\": \"$SECTION_ID\""
[ -n "$PROJECT_ID" ] && [ -z "$TASK_ID" ] && PAYLOAD="$PAYLOAD, \"project_id\": \"$PROJECT_ID\""

if [ -n "$DESCRIPTION" ]; then
  ESC_DESC=$(echo "$DESCRIPTION" | sed ':a;N;$!ba;s/\n/\\n/g' | sed 's/"/\\"/g')
  PAYLOAD="$PAYLOAD, \"description\": \"$ESC_DESC\""
fi

[ -n "$LABELS" ] && PAYLOAD="$PAYLOAD, \"labels\": $LABELS"
PAYLOAD="$PAYLOAD}"

if [ -n "$TASK_ID" ]; then
  ./scripts/todoist_api.sh "tasks/$TASK_ID" POST "$PAYLOAD"
else
  ./scripts/todoist_api.sh "tasks" POST "$PAYLOAD"
fi

#!/bin/bash
# scripts/add_comment.sh
# Usage: ./add_comment.sh <task_id> <comment_text>
TASK_ID=$1
TEXT=$2
ESC_TEXT=$(echo "$TEXT" | sed ':a;N;$!ba;s/\n/\\n/g' | sed 's/"/\\"/g')
PAYLOAD="{\"task_id\": \"$TASK_ID\", \"content\": \"$ESC_TEXT\"}"
./scripts/todoist_api.sh "comments" POST "$PAYLOAD"

Important: do not hardcode secrets into scripts in a repo. Prefer environment variables, a secrets manager, or your hosting environment.

Step 5: Store configuration as environment variables

Recommended variables:

• TODOIST_API_TOKEN
• TODOIST_PROJECT_ID
• TODOIST_SECTION_PROGRESS
• TODOIST_SECTION_WAITING
• TODOIST_SECTION_DONE

If you run OpenClaw on ClawRapid, store them in the deployment environment so the agent can access them without pasting tokens into chat.

Step 6: Define the operating rules (the contract)

You want consistent behavior. Add a short contract as persistent instructions.

Copy-paste prompt:

For every task I give you that will take more than 10 minutes:

1) Create a Todoist task in the "🟡 In Progress" section.
- Title: a short outcome-oriented name
- Description: your PLAN (steps), assumptions, and what "done" means

2) As you complete each milestone, add a Todoist comment with:
- timestamp
- what you did
- what is next
- any risk or blocker

3) If you are blocked waiting for me, move the task to "🟠 Waiting" and comment with what you need.

4) When finished, move the task to "🟢 Done" and comment a final summary with links to output files.

Logging policy:
- Log at milestones, not every micro-step.
- Combine related steps into one comment.

Recommended task template

A consistent template makes scanning effortless.

Title convention:

• [Build] Deploy analytics dashboard
• [Research] Pricing analysis for competitors
• [Content] Draft 5 use case articles

Description template:

• Objective
• Plan (numbered steps)
• Inputs needed (from you)
• Output location (files, links)
• Definition of done
• Risks

This is the “contract” you want to see before the agent starts.

Example workflows and prompts

Track a coding refactor

Refactor the authentication module.

Use Todoist visibility:
- Create an In Progress task with your plan.
- Log each milestone as a comment.
- If you need decisions from me, move to Waiting.

Constraints:
- Do not change external API routes.
- Prefer small commits.

Track deep research

Research the top 10 competitor landing pages for OpenClaw-style agents.

Use Todoist visibility. In the plan include:
- sources you will check
- the rubric for scoring
- output format (a markdown report)

Post progress comments as you fetch and summarize.

Track a content batch

Draft 5 blog posts about OpenClaw use cases.

Use Todoist visibility.
In the plan include:
- slugs
- target word count for each
- internal links you will include

Log each completed article as a comment with file paths.

Advanced upgrades

Upgrade 1: Add labels for type and priority

Use labels to segment runs:

• run:build
• run:research
• run:content

Then you can filter:

• all in-progress builds
• all blocked research

Upgrade 2: Create a “stalled run” heartbeat

A common pain: a run silently stalls.

A simple heartbeat can:

• find tasks in In Progress
• check last comment timestamp
• if no update in X hours, post a reminder to you

Policy suggestion:

• warn after 6 hours for active work
• warn after 24 hours for background work

Keep it conservative to avoid alert fatigue.

Upgrade 3: Add “definition of done” validation

When closing a task, require:

• output paths
• how to verify
• what changed

This makes “Done” meaningful.

Upgrade 4: Link Todoist tasks to project tracking events

If you run an event-driven project tracker (see /blog/openclaw-project-tracking):

• when a run starts, log a progress event
• when it completes, log another event with the output link

Todoist becomes the execution queue, and the project tracker becomes the truth timeline.

Troubleshooting and hard-earned lessons

“My task is created, but it never moves sections”

• Confirm you are setting section_id on the task and that the IDs are correct.
• Some Todoist setups require the task to be in the correct project first.

“Comments are not appearing”

• Make sure you are calling the /comments endpoint with task_id.
• Ensure JSON is valid and properly escaped (quotes and newlines).

“The agent spammed too many comments”

Adopt a logging policy:

• log at milestones
• group micro-steps
• include a short “next actions” list per comment

“Security: I do not want my token in logs”

• Keep tokens in environment variables.
• Avoid echoing curl commands.
• If you share logs, redact Authorization headers.

FAQ

Q: Do I need a dedicated Todoist project for this? A: Not strictly, but it helps. Keeping agent runs separated from personal tasks avoids noise and makes status scanning faster.

Q: Can I use labels instead of sections? A: Yes. Sections are simpler for state. Labels are better for categorization. Many people use both.

Q: How do I link one Todoist task to multiple outputs? A: Put canonical output links in the final comment, and update the description with a small “Outputs” list as you go.

Q: Can OpenClaw automatically detect a stalled task? A: Yes, via a heartbeat that checks the last update time. Start with a conservative threshold.

Q: What should go into the plan versus the comments? A: Put stable intent in the plan (steps, definition of done). Put execution details in comments (what happened, what changed, blockers).

Q: Does this replace a real project tracker? A: No. It is a visibility layer that makes the agent’s work less stressful and more auditable.

Example: what a good run looks like in Todoist

If you want this system to “feel” right, aim for a task that tells a complete story.

A good agent run task has:

• A title that describes an outcome, not an activity
• A description that states the plan and definition of done
• 3 to 8 milestone comments, not 40 micro-updates
• A final comment that links to outputs and explains how to verify

Example milestone comments (condensed):

1. 09:12 Started. Created branch feature/auth-refactor. Identified 3 modules that need changes. Next: update token validation.
2. 09:45 Implemented token validation refactor. Added tests for 4 edge cases. Next: update middleware wiring.
3. 10:20 Updated middleware wiring and ran test suite. One failure in integration tests. Next: fix failing test.
4. 10:42 Fixed integration test by updating mock fixtures. All tests passing locally. Next: push branch and open PR.
5. 11:05 Opened PR #123, added summary and rollout steps. Waiting for review.

Notice what is missing: no verbose logs, no stack traces, no copy-pasted terminal output. The goal is visibility, not telemetry.

If you want an even tighter workflow, you can adopt a “checkpoint every 30 minutes” policy for active work, and “checkpoint at each stage transition” policy for background work.

Next steps

Once you have transparency:

• Add a morning brief that surfaces the top 3 in-progress agent runs (see /blog/openclaw-morning-brief)
• Add event-driven project tracking for a durable timeline (see /blog/openclaw-project-tracking)
• If you want a “team” feel, route runs to specialized agents (see /blog/openclaw-multi-agent-team)

Want to deploy OpenClaw and start using this workflow today? Use the deploy form at the top of this article, then bookmark /blog/openclaw-use-cases for more battle-tested setups.